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Pyramiding QTLs controlling tolerance against drought, salinity, and submergence in rice through marker assisted breeding.

ABSTRACT: Increases in rice productivity are significantly hampered because of the increase in the occurrence of abiotic stresses, including drought, salinity, and submergence. Developing a rice variety with inherent tolerance against these major abiotic stresses will help achieve a sustained increase in rice production under unfavorable conditions. The present study was conducted to develop abiotic stress-tolerant rice genotypes in the genetic background of the popular rice variety Improved White Ponni (IWP) by introgressing major effect quantitative trait loci (QTLs) conferring tolerance against drought (qDTY1.1, qDTY2.1), salinity (Saltol), and submergence (Sub1) through a marker assisted backcross breeding approach. Genotyping of early generation backcrossed inbred lines (BILs) resulted in the identification of three progenies, 3-11-9-2, 3-11-11-1, and 3-11-11-2, possessing all four target QTLs and maximum recovery of the recurrent parent genome (88.46%). BILs exhibited consistent agronomic and grain quality characters compared to those of IWP and enhanced performance against dehydration, salinity, and submergence stress compared with the recurrent parent IWP. BILs exhibited enhanced tolerance against salinity during germination and increased shoot length, root length, and vigor index compared to those of IWP. All three BILs exhibited reduced symptoms of injury because of salinity (NaCl) and dehydration (PEG) than did IWP. At 12 days of submergence stress, BILs exhibited enhanced survival and greater recovery, whereas IWP failed completely. BILs were found to exhibit on par grain and cooking quality characteristics with their parents. Results of this study clearly demonstrated the effects of the target QTLs in reducing damage caused by drought, salinity, and submergence and lead to the development of a triple stress tolerant version of IWP.

SUBMITTER: Muthu V

PROVIDER: S-EPMC6946594 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND:Marker-assisted breeding will move forward from introgressing single/multiple genes governing a single trait to multiple genes governing multiple traits to combat emerging biotic and abiotic stresses related to climate change and to enhance rice productivity. MAS will need to address concerns about the population size needed to introgress together more than two genes/QTLs. In the present study, grain yield and genotypic data from different generations (F3 to F8) for five marker-assisted breeding programs were analyzed to understand the effectiveness of synergistic effect of phenotyping and genotyping in early generations on selection of better progenies. RESULTS:Based on class analysis of the QTL combinations, the identified superior QTL classes in F3/BC1F3/BC2F3 generations with positive QTL x QTL and QTL x background interactions that were captured through phenotyping maintained its superiority in yield under non-stress (NS) and reproductive-stage drought stress (RS) across advanced generations in all five studies. The marker-assisted selection breeding strategy combining both genotyping and phenotyping in early generation significantly reduced the number of genotypes to be carried forward. The strategy presented in this study providing genotyping and phenotyping cost savings of 25-68% compared with the traditional marker-assisted selection approach. The QTL classes, Sub1?+?qDTY 1.1 +?qDTY 2.1 ?+?qDTY 3.1 and Sub1?+?qDTY 2.1 ?+?qDTY 3.1 in Swarna-Sub1, Sub1?+?qDTY 1.1 ?+?qDTY 1.2 , Sub1?+?qDTY 1.1 ?+?qDTY 2.2 and Sub1?+?qDTY 2.2 ?+?qDTY 12.1 in IR64-Sub1, qDTY 2.2 ?+?qDTY 4.1 in Samba Mahsuri, Sub1?+?qDTY 3.1 ?+?qDTY 6.1 ?+?qDTY 6.2 and Sub1?+?qDTY 6.1 ?+?qDTY 6.2 in TDK1-Sub1 and qDTY 12.1 ?+?qDTY 3.1 and qDTY 2.2 ?+?qDTY 3.1 in MR219 had shown better and consistent performance under NS and RS across generations over other QTL classes. CONCLUSION:"Deployment of this procedure will save time and resources and will allow breeders to focus and advance only germplasm with high probability of improved performance. The identification of superior QTL classes and capture of positive QTL x QTL and QTL x background interactions in early generation and their consistent performance in subsequent generations across five backgrounds supports the efficacy of a combined MAS breeding strategy".

Project description:BackgroundOver the last decade genetic marker-based plant breeding strategies have gained increasing attention because genotyping technologies are no longer limiting. Now the challenge is to optimally use genetic markers in practical breeding schemes. For simple traits such as some disease resistances it is possible to target a fixed multi-locus allele configuration at a small number of causal or linked loci. Efficiently obtaining this genetic ideotype from a given set of parental genotypes is known as the marker-assisted gene pyramiding problem. Previous methods either imposed strong restrictions or used black box integer programming solutions, while this paper explores the power of an explicit heuristic approach that exploits the underlying genetic structure to prune the search space.ResultsGene Stacker is introduced as a novel approach to marker-assisted gene pyramiding, combining an explicit directed acyclic graph model with a pruned generation algorithm inspired by a simple exhaustive search. Both exact and heuristic pruning criteria are applied to reduce the number of generated schedules. It is shown that this approach can effectively be used to obtain good solutions for stacking problems of varying complexity. For more complex problems, the heuristics allow to obtain valuable approximations. For smaller problems, fewer heuristics can be applied, resulting in an interesting quality-runtime tradeoff. Gene Stacker is competitive with previous methods and often finds better and/or additional solutions within reasonable time, because of the powerful heuristics.ConclusionsThe proposed approach was confirmed to be feasible in combination with heuristics to cope with realistic, complex stacking problems. The inherent flexibility of this approach allows to easily address important breeding constraints so that the obtained schedules can be widely used in practice without major modifications. In addition, the ideas applied for Gene Stacker can be incorporated in and extended for a plant breeding context that e.g. also addresses complex quantitative traits or conservation of genetic background. Gene Stacker is freely available as open source software at http://genestacker.ugent.be . The website also provides documentation and examples of how to use Gene Stacker.

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Pyramiding QTLs controlling tolerance against drought, salinity, and submergence in rice through marker assisted breeding.

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